Comparative Evaluation of Typical Antipsychotic Haloperidol with Atypical Antipsychotics Olanzapine, Risperidone and Aripiprazole in the Treatment of Stable Schizophrenia in a Tertiary Care Teaching Hospital at Dehradun, Uttarakhand, India: A Randomised Clinical Trial
Bibliographic record
Abstract
the National Mental Health Survey 2015-16, the prevalence of schizophrenia and psychotic disorders in the Indian population is approximately 1.4%, with significant treatment gaps, especially in rural regions [7,8]. Factors such as stigma, limited access to mental healthcare and socioeconomic challenges exacerbate the burden of the disease [9,10]. Pharmacological management remains the cornerstone of schizophrenia treatment. FGAs such as haloperidol primarily target dopamine D2 receptors and are effective against positive symptoms, including hallucinations and delusions. However, their use is often limited by adverse effects such as EPS, tardive dyskinesia and hyperprolactinaemia [11,12]. The introduction of SGAs, including olanzapine, risperidone and aripiprazole, has significantly advanced schizophrenia management. SGAs target both dopamine and serotonin receptors, improving efficacy against both positive and negative symptoms, with a lower risk of neurological side-effects. Keywords: Adverse effects, Effects, Safety ABSTRACT Introduction: Schizophrenia, a chronic psychiatric disorder, significantly impacts patients’ quality of life through positive symptoms (e.g., hallucinations, delusions), negative symptoms (e.g., social withdrawal, emotional blunting) and cognitive impairments. The pharmacological treatment landscape has evolved from First-Generation Antipsychotics (FGAs) like haloperidol to Second-Generation Antipsychotics (SGAs), such as olanzapine, risperidone and aripiprazole, which aim to improve therapeutic outcomes while minimising adverse effects. However, comparative evaluations of efficacy and safety among these agents remain critical, especially in the Indian context. Aim: To compare the therapeutic efficacy and safety of the FGA haloperidol with the SGAs olanzapine, risperidone and aripiprazole in the management of stable schizophrenia. Materials and Methods: This randomised, clinical open-label, prospective study was conducted for one year which included 98 stable schizophrenia patients diagnosed according to the International Classification of Diseases -10 criteria. Participants were divided into four groups receiving haloperidol (n=24), olanzapine (n=25), risperidone (n=25), or aripiprazole (n=24). Psychometric assessments were performed using the Brief Psychiatric Rating Scale (BPRS), Positive and Negative Symptoms Scale (PANSS), Clinical Global Impression (CGI), and Calgary Depression Rating Scale (CDRS) at baseline and follow-up visits over 16 weeks. Adverse Drug Reactions (ADRs) were monitored using the World Health Organisation-Uppsala Monitoring Centre (WHO-UMC) Causality Assessment Scale. Statistical analysis included paired t-tests and Analysis of Variance (ANOVA), with significance set at p-value <0.05. Results: Olanzapine demonstrated the greatest efficacy, with significant improvements in BPRS and PANSS scores (p-value <0.0001), followed by risperidone and aripiprazole. Haloperidol showed efficacy in controlling positive symptoms but was less effective for negative and cognitive symptoms. ADRs were most frequent with haloperidol (57 events), primarily Extrapyramidal Symptoms (EPS), while SGAs exhibited better tolerability profiles with olanzapine showing the least ADRs (27 events). Weight gain and increased appetite were common among SGAs, whereas aripiprazole had the lowest metabolic disturbances. Conclusion: The study underscores the superior efficacy and safety profiles of SGAs, particularly olanzapine and risperidone, in managing stable schizophrenia. Haloperidol remains useful for acute symptom control but is less suitable for long-term therapy due to its adverse effects. These findings reinforce the importance of personalised treatment strategies to optimise schizophrenia management and improve patient outcomes.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.003 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.003 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.002 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.006 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".